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  2. Comparison of programming languages (array) - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_programming...

    In addition to support for vectorized arithmetic and relational operations, these languages also vectorize common mathematical functions such as sine. For example, if x is an array, then y = sin (x) will result in an array y whose elements are sine of the corresponding elements of the array x. Vectorized index operations are also supported.

  3. Comparison of programming languages (associative array)

    en.wikipedia.org/wiki/Comparison_of_programming...

    Finally, the GLib library also supports associative arrays, along with many other advanced data types and is the recommended implementation of the GNU Project. [3] Similar to GLib, Apple's cross-platform Core Foundation framework provides several basic data types. In particular, there are reference-counted CFDictionary and CFMutableDictionary.

  4. Associative array - Wikipedia

    en.wikipedia.org/wiki/Associative_array

    In mathematical terms, an associative array is a function with finite domain. [1] It supports 'lookup', 'remove', and 'insert' operations. The dictionary problem is the classic problem of designing efficient data structures that implement associative arrays. [2] The two major solutions to the dictionary problem are hash tables and search trees.

  5. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    More generally, there are d! possible orders for a given array, one for each permutation of dimensions (with row-major and column-order just 2 special cases), although the lists of stride values are not necessarily permutations of each other, e.g., in the 2-by-3 example above, the strides are (3,1) for row-major and (1,2) for column-major.

  6. Comparison of programming languages - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_programming...

    1960, IFIP WG 2.1, ISO [8] ALGOL 68: Application Yes No Yes Yes Yes No Concurrent Yes 1968, IFIP WG 2.1, GOST 27974-88, [9] Ateji PX: Parallel application No Yes No No No No pi calculus: No APL: Application, data processing: Yes Yes Yes Yes Yes Yes Array-oriented, tacit: Yes 1989, ISO Assembly language: General Yes No No No No No

  7. Merge algorithm - Wikipedia

    en.wikipedia.org/wiki/Merge_algorithm

    In the merge sort algorithm, this subroutine is typically used to merge two sub-arrays A[lo..mid], A[mid+1..hi] of a single array A. This can be done by copying the sub-arrays into a temporary array, then applying the merge algorithm above. [1] The allocation of a temporary array can be avoided, but at the expense of speed and programming ease.

  8. Array (data type) - Wikipedia

    en.wikipedia.org/wiki/Array_(data_type)

    In computer science, array is a data type that represents a collection of elements (values or variables), each selected by one or more indices (identifying keys) that can be computed at run time during program execution. Such a collection is usually called an array variable or array value. [1]

  9. 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.