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  2. Librsb - Wikipedia

    en.wikipedia.org/wiki/Librsb

    Sparse matrix-vector triangular solve. Sparse matrix-dense matrix triangular solve. Sparse matrix-sparse matrix multiplication. Elemental sparse matrix operations (scaling, add, etc.). Row-wise or column-wise scaling. Rows / columns extraction. An online empirical autotuning function. File input/output in the Matrix Market format.

  3. Matrix Template Library - Wikipedia

    en.wikipedia.org/wiki/Matrix_Template_Library

    The Matrix Template Library (MTL) is a linear algebra library for C++ programs. The MTL uses template programming , which considerably reduces the code length. All matrices and vectors are available in all classical numerical formats: float , double , complex<float> or complex<double> .

  4. Row- and column-major order - Wikipedia

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

    While the terms allude to the rows and columns of a two-dimensional array, i.e. a matrix, the orders can be generalized to arrays of any dimension by noting that the terms row-major and column-major are equivalent to lexicographic and colexicographic orders, respectively. It is also worth noting that matrices, being commonly represented as ...

  5. Matrix representation - Wikipedia

    en.wikipedia.org/wiki/Matrix_representation

    Matrix representation is a method used by a computer language to store column-vector matrices of more than one dimension in memory. Fortran and C use different schemes for their native arrays. Fortran uses "Column Major" ( AoS ), in which all the elements for a given column are stored contiguously in memory.

  6. Comparison of linear algebra libraries - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_linear...

    C++ template library; binds to optimized BLAS such as the Intel MKL; Includes matrix decompositions, non-linear solvers, and machine learning tooling Eigen: Benoît Jacob C++ 2008 3.4.0 / 08.2021 Free MPL2: Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms. Fastor [5]

  7. Sparse matrix - Wikipedia

    en.wikipedia.org/wiki/Sparse_matrix

    For an m × n matrix, the amount of memory required to store the matrix in this format is proportional to m × n (disregarding the fact that the dimensions of the matrix also need to be stored). In the case of a sparse matrix, substantial memory requirement reductions can be realized by storing only the non-zero entries.

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  9. Application binary interface - Wikipedia

    en.wikipedia.org/wiki/Application_binary_interface

    In contrast, an application programming interface (API) defines this access in source code, which is a relatively high-level, hardware-independent, often human-readable format. A common aspect of an ABI is the calling convention , which determines how data is provided as input to, or read as output from, computational routines.