Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Parallel Optimization of the SSABS Exact String-Matching Algorithm for Shared-Memory Multicore Systems Using POSIX Threads. |
| Συγγραφείς: |
AbdulRazzaq, Atheer Akram1 (AUTHOR) athproof@uoitc.edu.iq, Mezher, Ahmed Eskander1,2 (AUTHOR), AL-Jumaili, Ahmed Sabah Ahmed1 (AUTHOR), Tayyeh, Huda Kadhim3 (AUTHOR) |
| Πηγή: |
Ingénierie des Systèmes d'Information. Jul2026, Vol. 31 Issue 7, p2425-2434. 10p. |
| Θεματικοί όροι: |
*Parallel programming, *Scalability, Multicore processors, Benchmark problems (Computer science) |
| Περίληψη: |
Exact string matching remains a fundamental operation in many data-intensive applications, where increasing dataset sizes require efficient parallel processing solutions. This study presents a parallel optimization of the Sheik-Sumit-Anindya-Balakrishnan-Sekar (SSABS) exact string-matching algorithm for shared-memory multicore systems using the Portable Operating System Interface (POSIX) threads framework. The proposed implementation divides input text into independent segments with boundary overlap handling to preserve matching accuracy while enabling concurrent execution across multiple CPU cores. The performance of the parallel SSABS algorithm was evaluated using four benchmark datasets, including Extensible Markup Language (XML), Source, Protein, and DNA, with different pattern lengths and core configurations. Experimental results demonstrate that the parallel implementation consistently reduces execution time compared with the sequential version across all tested datasets. The source dataset achieved the shortest parallel execution time due to its larger alphabet size and more effective shift operations; the DNA dataset obtained the highest scalability performance, reaching a maximum speedup of 2.97 and the highest efficiency among the evaluated datasets. Further analysis revealed that increasing the number of cores improves acceleration but introduces synchronization and thread-management overhead, leading to performance saturation at higher core counts. These findings provide insights into the relationship between dataset characteristics, algorithm behavior, and multicore scalability, demonstrating the suitability of Pthreads-based parallelization for accelerating exact string-matching operations. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: |
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