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
ALGLIB is an open source numerical analysis library which may be used from C++, C#, FreePascal, Delphi, VBA.
ArrayFire is a high performance open source software library for parallel computing with an easy-to-use API.
IMSL Numerical Libraries are libraries of numerical analysis functionality implemented in standard programming languages like C, Java, C# .NET, Fortran, and Python.
The NAG Library is a collection of mathematical and statistical routines for multiple programming languages (C, C++, Fortran, Visual Basic, Java, Python and C#) and packages (MATLAB, Excel, R, LabVIEW).
GNU Octave is an open source high level programming language and library, including a command line interface and GUI, analogous to commercial alternatives such as Maple, MATLAB, Mathematica, etc. APIs, functions and libraries can be called from many platforms, including high level engineering programs, where functions are, in many cases, seamlessly interpreted and integrated in similar fashion to MATLAB. It also can be used with batch orientation.
librsb is an open source library for high performance sparse matrix computations providing multi-threaded primitives to build iterative solvers (implements also the Sparse BLAS standard). It can be used from C, C++, Fortran, and a dedicated GNU Octave package.
LabWindows/CVI is an ANSI C IDE that includes built-in libraries for analysis of raw measurement data, signal generation, windowing, filter functions, signal processing, linear algebra, array and complex operations, curve fitting and statistics.
Lis is a scalable parallel library for solving systems of linear equations and eigenvalue problems using iterative methods.
Intel MKL (Math Kernel Library) contains optimized math routines for science, engineering, and financial applications, and is written in C/C++ and Fortran. Core math functions include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier transforms, and vector math.
Intel IPP is a multi-threaded software library of functions for multimedia and data processing applications.
OpenBLAS is an open source implementation of the BLAS API with many hand-crafted optimizations for specific processor types. It performs similar to Intel MKL on Intel processors and higher on various others.
Advanced Simulation Library is free and open source hardware accelerated multiphysics simulation software with an OpenCL-based internal computational engine.
ALGLIB is an open source / commercial numerical analysis library with C++ version
Armadillo is a C++ linear algebra library (matrix and vector maths), aiming towards a good balance between speed and ease of use.[1] It employs template classes, and has optional links to BLAS and LAPACK. The syntax (API) is similar to MATLAB.
Blitz++ is a high-performance vector mathematics library written in C++.
Boost.uBLAS C++ libraries for numerical computation
deal.II is a library supporting all the finite element solution of partial differential equations.
Dlib is a modern C++ library with easy to use linear algebra and optimization tools which benefit from optimized BLAS and LAPACK libraries.
Eigen is a vector mathematics library with performance comparable with Intel's Math Kernel Library
Hermes Project: C++/Python library for rapid prototyping of space- and space-time adaptive hp-FEM solvers.
IML++ is a C++ library for solving linear systems of equations, capable of dealing with dense, sparse, and distributed matrices.
IT++ is a C++ library for linear algebra (matrices and vectors), signal processing and communications. Functionality similar to MATLAB and Octave.
Intel MKL, Intel Math Kernel Library (in C and C++), a library of optimized math routines for science, engineering, and financial applications, written in C/C++ and Fortran. Core math functions include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier transforms, and vector math.
mlpack is an open-source library for machine learning, exploiting C++ language features to provide maximum performance and flexibility while providing a simple and consistent API
MTL4 is a generic C++ template library providing sparse and dense BLAS functionality. MTL4 establishes an intuitive interface (similar to MATLAB) and broad applicability thanks to Generic programming.
OpenFOAM is an open-source C++ library for solving partial differential equations in computational fluid dynamics (CFD).
SU2 code is an open-source library for solving partial differential equations with the finite volume or finite element method.
Trilinos is an effort to develop algorithms and enabling technologies for the solution of large-scale, complex multi-physics engineering and scientific problems. It is a collection of packages.
Template Numerical Toolkit (TNT) linear algebra software in the public domain and entirely in the form of headers, from NIST. TNT was originally presented as a successor to Lapack++, Sparselib++, and IML++.[2]
Accord.NET is a collection of libraries for scientific computing, including numerical linear algebra, optimization, statistics, artificial neural networks, machine learning, signal processing and computer vision. LGPLv3, partly GPLv3.
AForge.NET is a computer vision and artificial intelligence library. It implements a number of genetic, fuzzy logic and machine learning algorithms with several architectures of artificial neural networks with corresponding training algorithms. LGPLv3 and partly GPLv3.
ALGLIB is an open source numerical analysis library with C# version. Dual licensed: GPLv2+, commercial license.
ILNumerics.Net Commercial high performance, typesafe numerical array classes and functions for general math, FFT and linear algebra, aims .NET/mono, 32&64 bit, script-like syntax in C#, 2D & 3D plot controls, efficient memory management.
IMSL Numerical Libraries have C# version (commercially licensed). IMSL .Net have announced end of life at the end of 2020.
Math.NET Numerics aims to provide methods and algorithms for numerical computations in science, engineering and everyday use. Covered topics include special functions, linear algebra, probability models, random numbers, interpolation, integral transforms and more. Free software under MIT/X11 license.
Measurement Studio is a commercial integrated suite UI controls and class libraries for use in developing test and measurement applications. The analysis class libraries provide various digital signal processing, signal filtering, signal generation, peak detection, and other general mathematical functionality.
The NAG Library has C# API. Commercially licensed.
NMath by CenterSpace Software: Commercial numerical component libraries for the .NET platform, including signal processing (FFT) classes, a linear algebra (LAPACK & BLAS) framework, and a statistics package.
EISPACK is a software library for numerical computation of eigenvalues and eigenvectors of matrices,[5] written in FORTRAN. It contains subroutines for calculating the eigenvalues of nine classes of matrices: complex general, complex Hermitian, real general, real symmetric, real symmetric banded, real symmetric tridiagonal, special real tridiagonal, generalized real, and generalized real symmetric matices.
IMSL Numerical Libraries are cross-platform libraries containing a comprehensive set of mathematical and statistical functions that can be embedded in a users application.
LINPACK is a software library for performing numerical linear algebra on digital computers.[8][9][10] It was written in Fortran by Jack Dongarra, Jim Bunch, Cleve Moler, and Pete Stewart, and was intended for use on supercomputers in the 1970s and early 1980s. It has been largely superseded by LAPACK, which will run more efficiently on modern architectures.
Lis is a scalable parallel library for solving systems of linear equations and eigenvalue problems using iterative methods.
MINPACK is a library of FORTRAN subroutines for the solving of systems of nonlinear equations, or the least squares minimization of the residual of a set of linear or nonlinear equations.
The NAG Fortran Library is a collection of mathematical and statistical routines for Fortran.
NOVAS is a software library for astrometry-related numerical computations. Both Fortran and C versions are available.
Netlib is a repository of scientific computing software which contains a large number of separate programs and libraries including BLAS, EISPACK, LAPACK and others.
JAMA, a numerical linear algebra toolkit for the Java programming language. No active development has taken place since 2005, but it still one of the more popular linear algebra packages in Java.
OCaml programming language has support for array programming in the standard library, also with an specific module named bigarrays for multi-dimensional, numerical arrays, with both C and Fortran layout options. A comprehensive support of numerical computations is provided by the library Owl Scientific Computing which provides methods for statistics, linear algebra (using OpenBLAS), differential equations, algorithmic differentiation, Fourier fast transform, or deep neural networks.[11] Other numerical libraries in OCaml are Lacaml that interfaces BLAS and LAPACK Fortran/C libraries, L-BFGS-ocaml (OCaml bindings for L-BFGS). For visualization there are libraries for plotting using PLplot, gnuplot or matplotlib.
Perl Data Language gives standard Perl the ability to compactly store and speedily manipulate the large N-dimensional data arrays.[12] It can perform complex and matrix maths, and has interfaces for the GNU Scientific Library, LINPACK, PROJ, and plotting with PGPLOT. There are libraries on CPAN adding support for the linear algebra library LAPACK,[13] the Fourier transform library FFTW,[14] and plotting with gnuplot,[15] and PLplot.[16]
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.
Pandas, a library for data manipulation and analysis.
SageMath is a large mathematical software application which integrates the work of nearly 100 free software projects and supports linear algebra, combinatorics, numerical mathematics, calculus, and more.[17]
SciPy,[18][19][20] a large BSD-licensed library of scientific tools. De facto standard for scientific computations in Python.
ScientificPython, a library with a different set of scientific tools
SymPy, a library based on New BSD license for symbolic computation. Features of Sympy range from basic symbolic arithmetic to calculus, algebra, discrete mathematics and quantum physics.
Others
XNUMBERS – multi-precision floating-Point computing and numerical methods for Microsoft Excel.
^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.
^Anderson, E., Bai, Z., Bischof, C., Blackford, S., Dongarra, J., Du Croz, J., ... & Sorensen, D. (1999). LAPACK Users' guide (Vol. 9). SIAM.
^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.
^Dongarra, J. J., Moler, C. B., Bunch, J. R., & Stewart, G. W. (1979). LINPACK users' guide. Society for Industrial and Applied Mathematics.
^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.
^Dongarra, J. J. (1987, June). The LINPACK benchmark: An explanation. In International Conference on Supercomputing (pp. 456-474). Springer, Berlin, Heidelberg.
