Awesome Scientific Computing
Useful resources for scientific computing and numerical analysis.
Scientific computing and numerical analysis are research fields that aim
to provide methods for solving large-scale problems from various areas of
science with the help of computers. Typical problems are ordinary and
partial differential equations (ODEs, PDEs), their discretizations, and
the solution of linear algebra problems arising from them.
Contents
Basic linear algebra
-
BLAS - Standard building
blocks for performing basic vector and matrix operations. (Fortran,
public domain,
GitHub)
-
OpenBLAS - Optimized BLAS library
based on GotoBLAS2. (C and Assembly, BSD,
GitHub)
-
BLIS - High-performance
BLAS-like dense linear algebra libraries. (C, BSD, GitHub)
-
LAPACK - Routines for
solving systems of linear equations, linear least-squares, eigenvalue
problems, etc. (Fortran, BSD,
GitHub)
-
Eigen
- C++ template library for linear algebra. (C++, MPL 2,
GitLab)
-
Ginkgo -
High-performance manycore linear algebra library, focus on sparse
systems. (C++, BSD,
GitHub)
-
blaze -
High-performance C++ math library for dense and sparse arithmetic. (C++,
BSD, Bitbucket)
-
PETSc - Parallel solution
of scientific applications modeled by PDEs. (C, 2-clause BSD,
GitLab)
-
DUNE Numerics - Toolbox for
solving PDEs with grid-based methods. (C++, GPL 2,
GitLab)
-
SciPy - Python modules for
statistics, optimization, integration, linear algebra, etc. (Python,
mostly BSD, GitHub)
-
NumPy - Fundamental package needed for
scientific computing with Python. (Python, BSD,
GitHub)
Finite Elements
-
FEniCS - Computing platform for
solving PDEs in Python and C++. (C++/Python, LGPL 3,
GitHub/Bitbucket)
-
libMesh - Framework for the
numerical simulation of PDEs using unstructured discretizations. (C++,
LGPL 2.1, GitHub)
-
deal.II - Software library supporting
the creation of finite element codes. (C++, LGPL 2.1,
GitHub)
-
Netgen/NGSolve - High performance
multiphysics finite element software. (C++, LGPL 2.1,
GitHub)
-
Firedrake - Automated
system for the solution of PDEs using the finite element method.
(Python, LGPL 3,
GitHub)
-
MOOSE - Multiphysics
Object Oriented Simulation Environment. (C++, LGPL 2.1,
GitHub)
-
MFEM - Free, lightweight, scalable C++
library for finite element methods. (C++, LGPL 2.1,
GitHub)
-
SfePy - Simple Finite Elements in
Python. (Python, BSD,
GitHub)
-
FreeFEM - High level
multiphysics-multimesh finite element language. (C++, LGPL,
GitHub)
-
libceed
- Code for Efficient Extensible Discretizations. (C, 2-clause BSD,
GitHub)
-
scikit-fem - Simple
finite element assemblers. (Python, BSD/GPL, GitHub)
Meshing
-
Gmsh - Three-dimensional finite element
mesh generator with pre- and post-processing facilities. (C++, GPL,
GitLab)
-
pygmsh - Python
interface for Gmsh. (Python, GPL 3, GitHub)
-
MeshPy -
Quality triangular and tetrahedral mesh generation. (Python, MIT,
GitHub)
-
meshio - I/O for various
mesh formats, file conversion. (Python, MIT, GitHub)
-
CGAL - Algorithms for computational
geometry. (C++, mixed LGPL/GPL,
GitHub)
-
pygalmesh - Python
interface for CGAL’s 3D meshing capabilities. (Python, GPL 3, GitHub)
-
mshr - Mesh
generation component of FEniCS. (Python, GPL 3, Bitbucket)
-
MOAB -
Representing and evaluating mesh data. (C++, mostly LGPL 3,
Bitbucket)
-
TetGen
- Quality tetrahedral mesh generator and 3D Delaunay triangulator. (C++,
AGPLv3)
-
Triangle -
Two-dimensional quality mesh generator and Delaunay triangulator. (C,
nonfree software)
-
optimesh - Triangular
mesh smoothing. (Python, GPL 3, GitHub)
-
distmesh - Simple
generator for unstructured triangular and tetrahedral meshes. (MATLAB,
GPL 3)
-
QuadriFlow
- A Scalable and Robust Method for Quadrangulation. (C++, BSD,
GitHub)
-
trimesh - Loading and using triangular
meshes with an emphasis on watertight surfaces. (Python, MIT,
GitHub)
-
dmsh - Simple generator
for unstructured triangular meshes, inspired by distmesh. (Python, GPL
3, GitHub)
-
pmp-library - Polygon mesh
processing library. (C++, MIT with Employer Disclaimer,
GitHub)
-
Mmg - Robust, open-source &
multidisciplinary software for remeshing. (C, LGPL 3,
GitHub)
-
meshplex - Fast tools
for simplex meshes. (Python, GPL 3, GitHub)
-
TetWild - Robust
Tetrahedral Meshing in the Wild. (C++, GPL 3,
GitHub)
-
TriWild -
Robust Triangulation with Curve Constraints. (C++, MPL 2,
GitHub)
-
fTetWild - Fast
Tetrahedral Meshing in the Wild. (C++, MPL 2,
GitHub)
-
SeismicMesh -
Parallel 2D/3D triangle/tetrahedral mesh generation with sliver removal.
(Python and C++, GPL 3, GitHub)
-
NetCDF -
Software libraries and data formats for array-oriented scientific data.
(C/C++/Fortran/Java/Python,
custom open-source license, GitHub)
-
HDF5 - Data model,
library, and file format for storing and managing data. (C/Fortran, BSD,
GitHub)
-
XDMF - eXtensible
Data Model and Format for data from High Performance Computing codes.
(C++, GitLab)
-
Zarr - Format for
the storage of chunked, compressed, N-dimensional arrays. (Python, MIT,
GitHub)
Sparse linear solvers
-
SuperLU -
Direct solution of large, sparse, nonsymmetric systems of linear
equations. (C, mostly BSD,
GitHub)
-
KryPy - Krylov
subspace methods for the solution of linear algebraic systems. (Python,
MIT, GitHub)
-
PyAMG - Algebraic Multigrid
Solvers in Python. (Python, MIT,
GitHub)
-
hypre
- Library of high-performance preconditioners and solvers. (C, Apache
2.0/MIT, GitHub)
Visualization
-
ParaView - Multi-platform data
analysis and visualization application based on VTK. (C++, BSD,
GitLab)
-
VTK - Process images and create 3D
computer graphics. (C++, BSD,
GitLab)
-
Mayavi - 3D
scientific data visualization and plotting in Python. (Python, BSD,
GitHub)
-
Polyscope - Viewer and user
interface for 3D geometry processing. (C++, MIT,
GitHub)
-
PyVista - 3D plotting and mesh
analysis through a streamlined interface for VTK. (Python, MIT,
GitHub)
-
vedo - Library for scientific
analysis and visualization of 3D objects based on VTK. (Python, MIT,
GitHub)
-
yt - A toolkit for analysis and
visualization of volumetric data. (Python, BSD,
GitHub)
-
F3D - Cross-platform, fast,
and minimalist 3D viewer with scientific visualization tools. (C++, BSD,
GitLab)
-
TTK - Topological
data analysis and visualization. (C++/Python, BSD,
GitHub)
-
FFTW - Discrete Fourier transforms in
one or more dimensions, of arbitrary input size, real and complex. (C,
GPL2, GitHub)
-
Qhull - Convex hull, Delaunay
triangulation, Voronoi diagram, halfspace intersection about a point,
etc. (C/C++,
custom open source license, GitHub)
-
GSL - Random number
generators, special functions, and least-squares fitting etc. (C/C++,
GPL 3, Savannah)
-
OpenFOAM - Free, open source CFD
(computational fluid dynamics) software. (C++, GPL 3,
GitHub)
-
quadpy - Numerical
integration (quadrature, cubature) in Python. (Python, GPL 3, GitHub)
-
FiPy - Finite-volume PDE
solver. (Python,
custom open-source license, GitHub)
-
accupy - Accurate sums
and dot products for Python. (Python, GPL 3, GitHub)
-
SLEPc - Scalable Library for
Eigenvalue Problem Computations. (C, 2-clause BSD,
GitLab)
-
Chebfun - Computing with
functions to about 15-digit accuracy. (MATLAB, BSD,
GitHub)
-
pyMOR - Model Order Reduction with
Python. (Python, 2-clause BSD,
GitHub)
-
cvxpy - Modeling language for
convex optimization problems. (Python, Apache 2.0,
GitHub)
-
PyWavelets -
Wavelet transforms in Python. (Python, MIT,
GitHub)
-
NFFT -
Nonequispaced fast Fourier transform. (C/MATLAB, GPL 2,
GitHub)
-
preCICE - Coupling library for
partitioned multi-physics simulations (FSI, CHT, and more). (C++, LGPL
3, GitHub)
-
orthopy - Compute
orthogonal polynomials efficiently. (Python, GPL 3, GitHub)
-
pyGAM -
Generalized Additive Models in Python. (Python, Apache 2.0,
GitHub)
-
Dedalus - Solve partial
differential equations with spectral methods. (Python, GPL 3,
GitHub)
-
PyGMO - Massively parallel
optimization. (Python/C++, MPL 2,
GitHub)
-
shenfun -
High-performance Python library for the spectral Galerkin method.
(Python, BSD-2,
GitHub)