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Parallel Sorting

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Introduction to HPC with MPI for Data Science

Part of the book series: Undergraduate Topics in Computer Science ((UTICS))

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Abstract

There exist plenty sequential algorithms to sort n numbers that achieve the optimal time complexity of \(\varTheta (n\log n)\). We can sort on parallel architectures with distributed memory by considering the granularity of local sorting.

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Notes

  1. 1.

    http://en.wikipedia.org/wiki/Ken_Batcher.

References

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Correspondence to Frank Nielsen .

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Nielsen, F. (2016). Parallel Sorting. In: Introduction to HPC with MPI for Data Science. Undergraduate Topics in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-21903-5_4

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  • DOI: https://doi.org/10.1007/978-3-319-21903-5_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21902-8

  • Online ISBN: 978-3-319-21903-5

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