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Parallel Processing of Sorting and Searching Algorithms Comparative Study

Author

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  • Saad AL-Azzam
  • Mohammad Qatawneh

Abstract

Recently, supercomputers structure and its software optimization have been popular subjects. Much of the software recently consumes a long period of time both to sort and search datasets, and thus optimizing these algorithms becomes a priority. In order to discover the most efficient sorting and searching algorithms for parallel processing units, one can compare CPU runtime as a performance index. In this paper, Quick, Bubble, and Merge sort algorithms have been chosen for comparison, as well as sequential and binary as search algorithms. Each one of the sort and search algorithms was tested in worst, average and best case scenarios. And each scenario was applied using multiple techniques (sequential, multithread, and parallel processing) on a various number of processors to spot differences and calculate speed up factor.The proposed solution aims to optimize the performance of a supercomputer focusing one-time efficiency; all tests were conducted by The IMAN1 supercomputer which is Jordan's first and fastest supercomputer.

Suggested Citation

  • Saad AL-Azzam & Mohammad Qatawneh, 2018. "Parallel Processing of Sorting and Searching Algorithms Comparative Study," Modern Applied Science, Canadian Center of Science and Education, vol. 12(4), pages 143-143, April.
    • Handle: RePEc:ibn:masjnl:v:12:y:2018:i:4:p:143
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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