Parallel implementation of maximum-shift algorithm using OpenMp

Abdulrazzaq, Atheer Akram; Hamad, Qusay Shihab; Taha, Ahmed

doi:10.11591/ijeecs.v22.i3.pp1529-1539

Cited by 4 publications

(3 citation statements)

References 20 publications

(24 reference statements)

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“…The XML dataset has achieved the defective results when utilizing the short pattern length, meanwhile the Protien database obtained extremely terrible results when utilizing the long pattern length. The speedup decreased when the alphabet size increased as the speedup is affected by the database type [24], [25].…”

Section: Discussion and Analysismentioning

confidence: 99%

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%

Parallel processing of E-Atheer algorithm using pthread paradigm

Abdulrazzaq

Fadhel

Alzubaidi

et al. 2023

IJEECS

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“…Efficiency is usually measured by the number of tasks that can be processed in a unit of time. The efficiency of the parallel algorithm is usually much higher than the efficiency of the sequential algorithm, thus making it more efficient in terms of resource utilization [29].…”

Section: The Run-time Speed-up and Efficiencymentioning

confidence: 99%

A parallel algorithm to find the exact solution of the travelling salesman problem

Al-Neama

Ahmed

Ali

2023

IJEECS

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The traveling salesman problem (TSP) is a problem in computer science that has been extensively studied and has a wide variety of real-world applications. It is considered an NP-hard issue since the only way to get a precise solution to it is to wait an exponentially long amount of time unless P=NP. Both accurate and heuristic algorithms exist to tackle this problem. The Branch-and-Bound algorithm (BnB) is often regarded as the most significant precise approach, despite the fact that it traverses, in the worst scenario, all potential tours in order to calculate the tour efficiently. This study proposed an efficient parallel algorithm to solve TSP by using a cluster multicore system. An exact algorithm will be used to get the optimal solution, and to expedite the search for the best path, we have employed a multi-threaded approach that capitalizes on the processing power of multiple CPU cores to concurrently process sub-problems.

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“…This ensures there is a proper balance of workload between different processors. A related approach using multicores was put forth by AbdulRazzaq et al [32] for designing an efficient string matching algorithm. A maximum shift algorithm has been designed for this purpose.…”

Section: Introductionmentioning

confidence: 99%

A multithreaded hybrid framework for mining frequent itemsets

Poovan

Acharya

Reddy³

2022

IJECE

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<p><span>Mining frequent itemsets is an area of data mining that has beguiled several researchers in recent years. Varied data structures such as Nodesets, DiffNodesets, NegNodesets, N-lists, and Diffsets are among a few that were employed to extract frequent items. However, most of these approaches fell short either in respect of run time or memory. Hybrid frameworks were formulated to repress these issues that encompass the deployment of two or more data structures to facilitate effective mining of frequent itemsets. Such an approach aims to exploit the advantages of either of the data structures while mitigating the problems of relying on either of them alone. However, limited efforts have been made to reinforce the efficiency of such frameworks. To address these issues this paper proposes a novel multithreaded hybrid framework comprising of NegNodesets and N-list structure that uses the multicore feature of today’s processors. While NegNodesets offer a concise representation of itemsets, N-lists rely on List intersection thereby speeding up the mining process. To optimize the extraction of frequent items a hash-based algorithm has been designed here to extract the resultant set of frequent items which further enhances the novelty of the framework.</span></p>

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Parallel implementation of maximum-shift algorithm using OpenMp

Cited by 4 publications

References 20 publications

Parallel processing of E-Atheer algorithm using pthread paradigm

Parallel processing of E-Atheer algorithm using pthread paradigm

A parallel algorithm to find the exact solution of the travelling salesman problem

A multithreaded hybrid framework for mining frequent itemsets

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