This is a list of numerical libraries, which are libraries used in software development for performing numerical calculations. It is not a complete listing but is instead a list of numerical libraries with articles on Wikipedia, with few exceptions.

The choice of a typical library depends on a range of requirements such as: desired features (e.g. large dimensional linear algebra, parallel computation, partial differential equations), licensing, readability of API, portability or platform/compiler dependence (e.g. Linux, Windows, Visual C++, GCC), performance, ease-of-use, continued support from developers, standard compliance, specialized optimization in code for specific application scenarios or even the size of the code-base to be installed.

Multi-language

C

C++

Delphi

.NET Framework languages C#, F#, VB.NET and PowerShell

Fortran

Java

  • SuanShu is an open-source Java math library. It supports numerical analysis, statistics and optimization.
  • Perl

    Python

    Others

    See also

    References

    1. ^ Sanderson, C., & Curtin, R. (2016). Armadillo: a template-based C++ library for linear algebra. Journal of Open Source Software, 1(2), 26.
    2. ^ David Ramel (2018-05-08). "Open Source, Cross-Platform ML.NET Simplifies Machine Learning -- Visual Studio Magazine". Visual Studio Magazine. Retrieved 2018-05-10.
    3. ^ Kareem Anderson (2017-05-09). "Microsoft debuts ML.NET cross-platform machine learning framework". On MSFT. Retrieved 2018-05-10.
    4. ^ Smith, B. T., Boyle, J. M., Garbow, B. S., Ikebe, Y., Klema, V. C., & Moler, C. B. (2013). Matrix eigensystem routines-EISPACK guide (Vol. 6). Springer.
    5. ^ Anderson, E., Bai, Z., Bischof, C., Blackford, S., Dongarra, J., Du Croz, J., ... & Sorensen, D. (1999). LAPACK Users' guide (Vol. 9). SIAM.
    6. ^ Demmel, J. (1989, December). LAPACK: A portable linear algebra library for supercomputers. In IEEE Control Systems Society Workshop on Computer-Aided Control System Design (pp. 1-7). IEEE.
    7. ^ Dongarra, J. J., Moler, C. B., Bunch, J. R., & Stewart, G. W. (1979). LINPACK users' guide. Society for Industrial and Applied Mathematics.
    8. ^ Dongarra, J. J., Luszczek, P., & Petitet, A. (2003). The LINPACK benchmark: past, present and future. Concurrency and Computation: practice and experience, 15(9), 803-820.
    9. ^ Dongarra, J. J. (1987, June). The LINPACK benchmark: An explanation. In International Conference on Supercomputing (pp. 456-474). Springer, Berlin, Heidelberg.
    10. ^ "Perl Data Language - metacpan.org". July 26, 2021.
    11. ^ "PDL::LinearAlgebra - Linear Algebra utils for PDL - metacpan.org". July 26, 2021.
    12. ^ "PDL::FFTW3 - PDL interface to the Fastest Fourier Transform in the West - metacpan.org". July 26, 2021.
    13. ^ "PDL::Graphics::Gnuplot - Gnuplot-based plotting for PDL - metacpan.org". July 26, 2021.
    14. ^ "PDL::Graphics::PLplot - Object-oriented interface from perl/PDL to the PLPLOT plotting library - metacpan.org". July 26, 2021.
    15. ^ Zimmermann, P., Casamayou, A., Cohen, N., Connan, G., Dumont, T., Fousse, L., ... & Bray, E. (2018). Computational Mathematics with SageMath. SIAM.
    16. ^ Jones, E., Oliphant, T., & Peterson, P. (2001). SciPy: Open source scientific tools for Python.
    17. ^ Bressert, E. (2012). SciPy and NumPy: an overview for developers. " O'Reilly Media, Inc.".
    18. ^ Blanco-Silva, F. J. (2013). Learning SciPy for numerical and scientific computing. Packt Publishing Ltd.
    19. ^ S.M. Rump: INTLAB – INTerval LABoratory. In Tibor Csendes, editor, Developments in Reliable Computing, pages 77–104. Kluwer Academic Publishers, Dordrecht, 1999.
    20. ^ Moore, R. E., Kearfott, R. B., & Cloud, M. J. (2009). Introduction to Interval Analysis. Society for Industrial and Applied Mathematics.
    21. ^ Rump, S. M. (2010). Verification methods: Rigorous results using floating-point arithmetic. Acta Numerica, 19, 287–449.
    22. ^ Hargreaves, G. I. (2002). Interval analysis in MATLAB. Numerical Algorithms, (2009.1).