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SciML / OrdinaryDiffEq.jl

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
https://diffeq.sciml.ai/latest/
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Parallel ODE Solvers #34

Open ChrisRackauckas opened 7 years ago

ChrisRackauckas commented 7 years ago

This is a good SE post for explaining the difference between the major groups.

Here is another reference for the differences .

Maybe we should write a wrapper to PFASST.

brandonkrull commented 6 years ago

I'm currently a postdoc working on pfasst-related algorithms in the context of symplectic integrators with the original authors of pypfasst (linked in original issue post). Pypfasst is deprecated, and there are really no other options in terms of wrapping around python code. Almost all PFASST algorithms are implemented in some kind of compiled language. I'm looking to take a stab at implementing it from scratch here.

ChrisRackauckas commented 6 years ago

Alright cool, sounds like a good plan. Let me know if you need anything. Our devdocs should be helpful if you want to get it into OrdinaryDiffEq.jl quickly: http://devdocs.juliadiffeq.org/latest/