Abstract
This paper discusses a parallel quicksort algorithm that is cost optimal, in average, using O(n/log(n)) processors. The cost optimality is mainly due to a cost optimal partitioning algorithm that utilizes all the processors when partitioning the array. A temporary array of the same size as the original array is needed during the partitioning process. The prefix sums are used to determine where a processor can copy its data.
We will prove that the algorithm has an average case complexity O(log2n), where n is the size of the data array. We will also discuss the implementation of our algorithm on a shared memory parallel computer and demonstrate that it outperforms other O(log2n) parallel sorting algorithms. In addition, it outperforms the sequential quicksort algorithm starting with two processors.
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Liu, J., Knowles, C., Davis, A.B. (2005). A Cost Optimal Parallel Quicksorting and Its Implementation on a Shared Memory Parallel Computer. In: Pan, Y., Chen, D., Guo, M., Cao, J., Dongarra, J. (eds) Parallel and Distributed Processing and Applications. ISPA 2005. Lecture Notes in Computer Science, vol 3758. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11576235_51
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DOI: https://doi.org/10.1007/11576235_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29769-7
Online ISBN: 978-3-540-32100-2
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