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  2. Pancake sorting - Wikipedia

    en.wikipedia.org/wiki/Pancake_sorting

    The simplest pancake sorting algorithm performs at most 2n − 3 flips. In this algorithm, a kind of selection sort , we bring the largest pancake not yet sorted to the top with one flip; take it down to its final position with one more flip; and repeat this process for the remaining pancakes.

  3. Method of Four Russians - Wikipedia

    en.wikipedia.org/wiki/Method_of_Four_Russians

    Algorithms to which the Method of Four Russians may be applied include: computing the transitive closure of a graph, Boolean matrix multiplication, edit distance calculation, sequence alignment, index calculation for binary jumbled pattern matching. In each of these cases it speeds up the algorithm by one or two logarithmic factors.

  4. 2–3–4 tree - Wikipedia

    en.wikipedia.org/wiki/2–3–4_tree

    In computer science, a 2–3–4 tree (also called a 2–4 tree) is a self-balancing data structure that can be used to implement dictionaries. The numbers mean a tree where every node with children (internal node) has either two, three, or four child nodes: a 2-node has one data element, and if internal has two child nodes;

  5. Change-making problem - Wikipedia

    en.wikipedia.org/wiki/Change-making_problem

    Another example is attempting to make 40 US cents without nickels (denomination 25, 10, 1) with similar result — the greedy chooses seven coins (25, 10, and 5 × 1), but the optimal is four (4 × 10). A coin system is called "canonical" if the greedy algorithm always solves its change-making problem optimally.

  6. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.

  7. Bitonic sorter - Wikipedia

    en.wikipedia.org/wiki/Bitonic_sorter

    Bitonic mergesort is a parallel algorithm for sorting. It is also used as a construction method for building a sorting network.The algorithm was devised by Ken Batcher.The resulting sorting networks consist of (⁡ ()) comparators and have a delay of (⁡ ()), where is the number of items to be sorted. [1]

  8. Flip-flop (programming) - Wikipedia

    en.wikipedia.org/wiki/Flip-flop_(programming)

    For example, in Perl each flip-flop operator has its own state, shared among all the threads, [4] the other programming languages do the same. To work around this limitation, the flip-flop operator would have to be modeled as an abstract data type, parameterized with: a predicate that tells whether to switch the flip-flop on,

  9. Fisher–Yates shuffle - Wikipedia

    en.wikipedia.org/wiki/Fisher–Yates_shuffle

    The algorithm generates a random permutations uniformly so long as the hardware operates in a fair manner. In 2015, Bacher et al. produced MERGESHUFFLE, an algorithm that divides the array into blocks of roughly equal size, uses Fisher—Yates to shuffle each block, and then uses a random merge recursively to give the shuffled array. [12]