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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

Lightweight, general, scalable C++ library for finite element methods

Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.

The development repository for the deal.II finite element library

  • finite-elements
  • c-plus-plus
  • fem
  • hpc

C++ library for solving large sparse linear systems with algebraic multigrid method

  • amg
  • c-plus-plus
  • sparse-linear-systems
  • opencl

VexCL is a C++ vector expression template library for OpenCL/CUDA/OpenMP

  • opencl
  • cuda
  • c-plus-plus
  • gpgpu

A Python native dynamical system simulation framework in the block diagram paradigm.

  • blockdiagram
  • control-systems
  • hierarchical-modeling
  • nonlinear-dynamics

Exascale multiphase flow solver — 2025 Gordon Bell Prize Finalist | 200T grid points on 43K+ GPUs

  • gpu
  • exascale
  • cfd
  • fortran

The fastest automatic differentiation library for C++, with Python bindings. Forward, adjoint and higher-order derivatives, checkpointing, Eigen support and JIT. Reproducible benchmarks against CppAD, Adept and autodiff.

  • automatic-differentiation
  • aad
  • algorithmic-differentiation
  • autodiff