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  2. List of numerical libraries - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_libraries

    Matrix Toolkit Java is a linear algebra library based on BLAS and LAPACK. ojAlgo is an open source Java library for mathematics, linear algebra and optimisation. exp4j is a small Java library for evaluation of mathematical expressions. SuanShu is an open-source Java math library. It supports numerical analysis, statistics and optimization.

  3. Java Excel API - Wikipedia

    en.wikipedia.org/wiki/Java_Excel_API

    Java Excel API (a.k.a. JXL ... {// Closing the writable work book wwbCopy ... Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; ...

  4. Comparison of linear algebra libraries - Wikipedia

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

    5.0.0 / 04.2022 Free MIT License: C# numerical analysis library with linear algebra support Matrix Template Library: Jeremy Siek, Peter Gottschling, Andrew Lumsdaine, et al. C++ 1998 4.0 / 2018 Free Boost Software License High-performance C++ linear algebra library based on Generic programming: NAG Numerical Library: The Numerical Algorithms Group

  5. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    To avoid installing the large SciPy package just to get an array object, this new package was separated and called NumPy. Support for Python 3 was added in 2011 with NumPy version 1.5.0. [15] In 2011, PyPy started development on an implementation of the NumPy API for PyPy. [16] As of 2023, it is not yet fully compatible with NumPy. [17]

  6. Internal rate of return - Wikipedia

    en.wikipedia.org/wiki/Internal_rate_of_return

    In this case, it is not even clear whether a high or a low IRR is better. There may even be multiple real IRRs for a single project, like in the example 0% as well as 10%. Examples of this type of project are strip mines and nuclear power plants, where there is usually a large cash outflow at the end of the project.

  7. 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).

  8. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    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. CuPy supports Nvidia CUDA GPU platform, and AMD ROCm GPU platform starting in v9.0. [4] [5] CuPy has been initially developed as a backend of Chainer deep learning framework, and later established as an independent project in ...

  9. Array programming - Wikipedia

    en.wikipedia.org/wiki/Array_programming

    The cross product operation is an example of a vector rank function because it operates on vectors, not scalars. Matrix multiplication is an example of a 2-rank function, because it operates on 2-dimensional objects (matrices). Collapse operators reduce the dimensionality of an input data array by one or more dimensions. For example, summing ...