I’m working to optimize a solver for a large, stiff, system of differential equations using DifferentialEquations.jl. I’ve been following through the guide on Code Optimization in the documentation, and have been trying to minimize my allocations. I’m using QNDF() as my solver and I’ve found that I …

[image] brynn: I’ve found that I can’t just preallocate all of my arrays because u and du change type from Vector{Float64} to something of type Float64(::ForwardDiff.Dual{ForwardDiff.Tag{OrdinaryDiffEq.OrdinaryDiffEqTag, Float64}, Float64, 12}} Check out PreallocationTools.jl. See the FAQ on …

Autodifferencing and type stability in DifferentialEquations.jl

New to Julia

ChrisRackauckas January 17, 2022, 10:55pm 5

Check out PreallocationTools.jl. See the FAQ on this.

https://diffeq.sciml.ai/stable/basics/faq/#I-get-Dual-number-errors-when-I-solve-my-ODE-with-Rosenbrock-or-SDIRK-methods

I should probably add an example on this to that tutorial.

1 Like

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Autodifferencing and type stability in DifferentialEquations.jl

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