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  2. 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.

  3. 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.

  4. Comparison of numerical-analysis software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_numerical...

    FOSS statistics program, intended as an alternative to IBM SPSS Statistics. [Note 2] R: R Foundation 1997 1997 4.3.2 31 October 2023: Free GPL: Primarily for statistics, but there are many interfaces to open-source numerical software SageMath: William Stein: 2005 10.2 3 December 2023: Free GPL: Programmable, includes computer algebra, 2D+3D ...

  5. Google JAX - Wikipedia

    en.wikipedia.org/wiki/Google_JAX

    JAX is a machine learning framework for transforming numerical functions developed by Google with some contributions from Nvidia. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).

  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. List of numerical analysis topics - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_analysis...

    Hilbert matrix — example of a matrix which is extremely ill-conditioned (and thus difficult to handle) Wilkinson matrix — example of a symmetric tridiagonal matrix with pairs of nearly, but not exactly, equal eigenvalues; Convergent matrix — square matrix whose successive powers approach the zero matrix; Algorithms for matrix multiplication:

  8. Comparison of linear algebra libraries - Wikipedia

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

    High-performance C++ linear algebra library based on Generic programming: NAG Numerical Library: The Numerical Algorithms Group: C, Fortran 1971 many components Non-free Proprietary General purpose numerical analysis library. NMath: CenterSpace Software: C# 2003 7.1 / 12.2019 Non-free Proprietary Math and statistical libraries for the .NET ...

  9. Comparison of programming languages (list comprehension)

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

    List comprehension is a syntactic construct available in some programming languages for creating a list based on existing lists. It follows the form of the mathematical set-builder notation (set comprehension) as distinct from the use of map and filter functions.