Parallel String Sorting Algorithm Improves Efficiency
String sorting is a fundamental operation in various data-intensive applications, ranging from bioinformatics to database indexing. However, parallelizing string sorting remains challenging due to irregular memory access patterns, which often lead to inefficient cache utilization. This paper introduces the Parallel N-Deque Partition Dual-Deque Merge string sorting algorithm, which is evaluated against several state-of-the-art parallel sorting techniques. It utilizes a paralle
A new parallel string sorting algorithm has been developed to enhance performance in data-heavy applications. The method uses a block-based approach to divide data into smaller segments for independent processing. It leverages the N-Deque structure and OpenMP scheduling for better execution. The algorithm was tested on two different processors, showing significant speed improvements. Results indicated a 5.25 times faster performance on Apple M2 and 11.92 times on Intel Xeon Gold 6142. The algorithm's efficiency also depends on factors like data size and scheduling methods. These improvements can lead to better performance in applications requiring fast data processing. This advancement could influence future developments in parallel computing and data management.
It offers a more efficient way to handle large-scale string sorting, which is critical for many computing tasks.
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