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CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python, Matlab/Octave, Julia or Javascript
LAPACK development repository
Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.
A header-only C++ library for large scale eigenvalue problems
V library to develop Artificial Intelligence and High-Performance Scientific Computations
Correctly rounded decimals for Go
ODE system solver made simple. For IVPs (initial value problems).
Utility library to pretty print physical values in proper metric units
This is a class module in beta state to implement computations with large integers and reals/rationals numbers, while proposing representation of numerical values as scientific notation, allowing to obtain several cohorts for the same number (a lot of fun!).