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  2. Merge sort - Wikipedia

    en.wikipedia.org/wiki/Merge_sort

    Merge sort parallelizes well due to the use of the divide-and-conquer method. Several different parallel variants of the algorithm have been developed over the years. Some parallel merge sort algorithms are strongly related to the sequential top-down merge algorithm while others have a different general structure and use the K-way merge method.

  3. k-way merge algorithm - Wikipedia

    en.wikipedia.org/wiki/K-way_merge_algorithm

    k-way merge algorithms usually take place in the second stage of external sorting algorithms, much like they do for merge sort. A multiway merge allows for the files outside of memory to be merged in fewer passes than in a binary merge. If there are 6 runs that need be merged then a binary merge would need to take 3 merge passes, as opposed to ...

  4. Merge algorithm - Wikipedia

    en.wikipedia.org/wiki/Merge_algorithm

    A graph exemplifying merge sort. Two red arrows starting from the same node indicate a split, while two green arrows ending at the same node correspond to an execution of the merge algorithm. The merge algorithm plays a critical role in the merge sort algorithm, a comparison-based sorting algorithm. Conceptually, the merge sort algorithm ...

  5. External sorting - Wikipedia

    en.wikipedia.org/wiki/External_sorting

    The previous example is a two-pass sort: first sort, then merge. The sort ends with a single k -way merge, rather than a series of two-way merge passes as in a typical in-memory merge sort. This is because each merge pass reads and writes every value from and to disk, so reducing the number of passes more than compensates for the additional ...

  6. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    If a problem can be solved by combining optimal solutions to non-overlapping sub-problems, the strategy is called "divide and conquer" instead. [1] This is why merge sort and quick sort are not classified as dynamic programming problems.

  7. Fork–join model - Wikipedia

    en.wikipedia.org/wiki/Fork–join_model

    The simple parallel merge sort of CLRS is a fork–join algorithm. [5]mergesort(A, lo, hi): if lo < hi: // at least one element of input mid = ⌊lo + (hi - lo) / 2⌋ fork mergesort(A, lo, mid) // process (potentially) in parallel with main task mergesort(A, mid, hi) // main task handles second recursion join merge(A, lo, mid, hi)

  8. Block sort - Wikipedia

    en.wikipedia.org/wiki/Block_Sort

    Block sort, or block merge sort, is a sorting algorithm combining at least two merge operations with an insertion sort to arrive at O(n log n) (see Big O notation) in-place stable sorting time. It gets its name from the observation that merging two sorted lists, A and B , is equivalent to breaking A into evenly sized blocks , inserting each A ...

  9. Polyphase merge sort - Wikipedia

    en.wikipedia.org/wiki/Polyphase_merge_sort

    A polyphase merge sort is a variation of a bottom-up merge sort that sorts a list using an initial uneven distribution of sub-lists (runs), primarily used for external sorting, and is more efficient than an ordinary merge sort when there are fewer than eight external working files (such as a tape drive or a file on a hard drive).