enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Comparison of linear algebra libraries - Wikipedia

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

    Numerical linear algebra library with long history librsb: Michele Martone C, Fortran, M4 2011 1.2.0 / 09.2016 Free GPL: High-performance multi-threaded primitives for large sparse matrices. Support operations for iterative solvers: multiplication, triangular solve, scaling, matrix I/O, matrix rendering.

  3. Cholesky decomposition - Wikipedia

    en.wikipedia.org/wiki/Cholesky_decomposition

    In linear algebra, the Cholesky decomposition or Cholesky factorization (pronounced / ʃ ə ˈ l ɛ s k i / shə-LES-kee) is a decomposition of a Hermitian, positive-definite matrix into the product of a lower triangular matrix and its conjugate transpose, which is useful for efficient numerical solutions, e.g., Monte Carlo simulations.

  4. Sparse matrix - Wikipedia

    en.wikipedia.org/wiki/Sparse_matrix

    SciPy provides support for several sparse matrix formats, linear algebra, and solvers. ALGLIB is a C++ and C# library with sparse linear algebra support; ARPACK Fortran 77 library for sparse matrix diagonalization and manipulation, using the Arnoldi algorithm; SLEPc Library for solution of large scale linear systems and sparse matrices

  5. SciPy - Wikipedia

    en.wikipedia.org/wiki/SciPy

    SciPy (pronounced / ˈ s aɪ p aɪ / "sigh pie" [3]) is a free and open-source Python library used for scientific computing and technical computing. [4]SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.

  6. Basic Linear Algebra Subprograms - Wikipedia

    en.wikipedia.org/wiki/Basic_Linear_Algebra...

    The library routines would also be better than average implementations; matrix algorithms, for example, might use full pivoting to get better numerical accuracy. The library routines would also have more efficient routines. For example, a library may include a program to solve a matrix that is upper triangular.

  7. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    The SciPy scientific library, for instance, uses HiGHS as its LP solver [13] from release 1.6.0 [14] and the HiGHS MIP solver for discrete optimization from release 1.9.0. [15] As well as offering an interface to HiGHS, the JuMP modelling language for Julia [16] also describes the specific use of HiGHS in its user documentation. [17]

  8. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    API to MATLAB and Python. Solve example Linear Programming (LP) problems through MATLAB, Python, or a web-interface. CPLEX: Popular solver with an API for several programming languages, and also has a modelling language and works with AIMMS, AMPL, GAMS, MPL, OpenOpt, OPL Development Studio, and TOMLAB. Free for academic use. Excel Solver Function

  9. Successive over-relaxation - Wikipedia

    en.wikipedia.org/wiki/Successive_over-relaxation

    It was devised simultaneously by David M. Young Jr. and by Stanley P. Frankel in 1950 for the purpose of automatically solving linear systems on digital computers. Over-relaxation methods had been used before the work of Young and Frankel. An example is the method of Lewis Fry Richardson, and the methods developed by R. V. Southwell.