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  2. Comparison of linear algebra libraries - Wikipedia

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

    C, Java, C#, Fortran, Python 1970 many components Non-free Proprietary General purpose numerical analysis library. LAPACK [7] [8] Fortran 1992 3.12.0 / 11.2023 Free 3-clause BSD: Numerical linear algebra library with long history librsb: Michele Martone C, Fortran, M4 2011 1.2.0 / 09.2016 Free GPL

  3. 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.

  4. List of numerical libraries - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_libraries

    NumPy, a BSD-licensed library that adds support for the manipulation of large, multi-dimensional arrays and matrices; it also includes a large collection of high-level mathematical functions. NumPy serves as the backbone for a number of other numerical libraries, notably SciPy. De facto standard for matrix/tensor operations in Python.

  5. Power iteration - Wikipedia

    en.wikipedia.org/wiki/Power_iteration

    #!/usr/bin/env python3 import numpy as np def power_iteration (A, num_iterations: int): # Ideally choose a random vector # To decrease the chance that our vector # Is orthogonal to the eigenvector b_k = np. random. rand (A. shape [1]) for _ in range (num_iterations): # calculate the matrix-by-vector product Ab b_k1 = np. dot (A, b_k) # calculate the norm b_k1_norm = np. linalg. norm (b_k1 ...

  6. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]

  7. Basic Linear Algebra Subprograms - Wikipedia

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

    Basic Linear Algebra Subprograms (BLAS) is a specification that prescribes a set of low-level routines for performing common linear algebra operations such as vector addition, scalar multiplication, dot products, linear combinations, and matrix multiplication.

  8. Brent's method - Wikipedia

    en.wikipedia.org/wiki/Brent's_method

    The Boost (C++ libraries) implements two algorithms based on Brent's method in C++ in the Math toolkit: Function minimization at minima.hpp with an example locating function minima . Root finding implements the newer TOMS748, a more modern and efficient algorithm than Brent's original, at TOMS748 , and Boost.Math rooting finding that uses ...

  9. Outer product - Wikipedia

    en.wikipedia.org/wiki/Outer_product

    In MATLAB, the function kron (A, B) is used for this product. These often generalize to multi-dimensional arguments, and more than two arguments. In the Python library NumPy, the outer product can be computed with function np.outer(). [8] In contrast, np.kron results in a flat array.