Assimulo offers 14 solvers with good documentation for explicit and implicit problems.


  • DifferentialEquations.jl offers a unified interface to about 300 different solvers from about a dozen different categories for a large range of problems. It wraps many existing open-source and commercial solvers, that have been implemented in C++ or Fortran and adds a growing number of native Julia solvers, many of them state-of-the-art.
  • ModelingToolkit.jl is an acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations.
  • KiteModels.jl implements kite models, connected to a tether for airborne wind energy applications. It uses the same algorithms as this tutorial, but it is not (yet) using ModelingToolkit.
  • Working with Julia projects A must-read before creating your first project.

Scientific papers