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  • 05:15

    ChrisRackauckas on master

    Documentation changes Stylisti… Merge pull request #285 from mk… (compare)

  • 05:15
    ChrisRackauckas closed #285
  • 01:20
    mkg33 opened #285
  • 00:24

    github-actions[bot] on v5.25.0

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  • Oct 14 21:44
    shashi synchronize #518
  • Oct 14 21:44

    shashi on symutils3

    Fix ReactionSystems tests Co-a… Fix state extraction Co-author… (compare)

  • Oct 14 19:42
    shashi synchronize #518
  • Oct 14 19:42

    shashi on symutils3

    FIXED ismassaction FINALLY Co-… (compare)

  • Oct 14 19:33

    ChrisRackauckas on dstest

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  • Oct 14 19:33

    ChrisRackauckas on master

    add a downstream test on DelayD… fix spelling don't use a non-constant global and 4 more (compare)

  • Oct 14 19:33
    ChrisRackauckas closed #1290
  • Oct 14 17:53
    seadra commented #676
  • Oct 14 17:52
    seadra commented #676
  • Oct 14 17:45
    seadra commented #676
  • Oct 14 17:33
    yewalenikhil65 starred SciML/ModelingToolkit.jl
  • Oct 14 17:30
    yewalenikhil65 starred SciML/DiffEqDocs.jl
  • Oct 14 17:30
    yewalenikhil65 starred SciML/Catalyst.jl
  • Oct 14 16:55
    ChrisRackauckas reopened #1290
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[slack] <torkel.loman> I see, will have a go at it.
[slack] <chrisrackauckas> oh yeah, MassActionJump has something tricky here.
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[slack] <Peter J> can I use DiscreteProblem with DiffEqGPU? it doesn't seem to be work by just giving EnsembleProblem one
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[slack] <chrisrackauckas> No, but that would be easy to add.
abstractingagent
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I would imagine embedding this in some kind of specialized neural ode architecture would be an interesting approach for discovering reaction kinetics from data and other dynamical systems
I wonder if this can be integrated with modelingtoolkit and diffeqflux
Feels like sindy with the dictionary being learnable as well
abstractingagent
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Maybe a recursive neural network to exploit it's tree structure
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[slack] <chrisrackauckas> yeah it's an interesting approach
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abstractingagent
@abstractingagent
You think adding meijer g function functionality to modelingtoolkit would be a good functionality add?
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[slack] <chrisrackauckas> would it not already exist through SpecialFunctions.jl?
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[slack] <isaacsas> @torkel.loman Were you able to get this working?
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[slack] <isaacsas> It looks like you want to modify integrator.cb.affect!.ma_jumps.scaled_rates[rxidx]
[slack] <isaacsas> We should really add a function that gets at this more easily.
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[slack] <torkel.loman> Is it intentional that remak() doesn't work on JumpProblems, and only on DiscreteProblems?
[slack] <chrisrackauckas> it's known but not intentional
[slack] <chrisrackauckas> it needs a fix.
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[slack] <torkel.loman> Yeah, I realised that if I where to make a general method for this, especially when there might be a mix of mass action and constant rate jumps it would just be a mess.
[slack] <torkel.loman> It was just much easier to make a method which solved it until the time point of the callback and took the values at the last time point as initial condition to another simulation, but with modified parameters.
[slack] <torkel.loman> It's not super pretty, but works well enough for my simple purposes.
(biggest problem is to run it in monte carlo, where I lose performance, but it is not of that much importance in this case)
[slack] <torkel.loman> But yes, some way of enabling one to modify these kinds of things with callbacks as easily for continuous problems should probably be a long term goal.
[slack] <torkel.loman> ok, cheers. I'll skip out on writing a report on it then
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[slack] <ashton.bradley> I don’t seem to get multithreading by default for a sparse matrix ode problem. If I used a semi linear formulation, would those Krylov methods use all cores?
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[slack] <chrisrackauckas> only in the internal QR which is a small portion of the calculation.
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[slack] <ashton.bradley> Ok... what’s the bottleneck? My colleague has some simple FORTRAN code to solve a pde, and its toasting Julia using openmp and very simple integration methods. What am I missing?
[slack] <chrisrackauckas> did you profile it?
[slack] <chrisrackauckas> same integration method?
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[slack] <ashton.bradley> I wasn’t able to entirely yet due to complex, but he is using crank Nicholson (trapezoid), gets >800% cpu on an 8 core machine, and about 10 times faster than single core TSit5
[slack] <ashton.bradley> So I wast able to use identical method, but I figure TSit5 should represent pretty well (?)
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[slack] <chrisrackauckas> Not if it's a PDE
[slack] <chrisrackauckas> Tsit5 is only for non-stiff equations
[slack] <chrisrackauckas> Use Trapezoid if you want to compare to Trapezoid?
[slack] <chrisrackauckas> what's he parallelizing? The Jacobian calculation?
[slack] <chrisrackauckas> Did you use auto-sparsity and all of that?
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[slack] <ashton.bradley> Trapezoid doesn’t allow complex variables
[slack] <ashton.bradley> I didn’t use auto-sparsity… maybe I should try that next
[slack] <chrisrackauckas> use finite differencing
[slack] <chrisrackauckas> autodiff is the issue, not Trapezoid
[slack] <ashton.bradley> do you mean DiffEqOperators ?
[slack] <chrisrackauckas> no
[slack] <chrisrackauckas> Trapezoid(autodiff=false)
[slack] <ashton.bradley> (it is already a finite difference method)
[slack] <ashton.bradley> ah, ok.
[slack] <chrisrackauckas> and are you also comparing the integration error?
[slack] <ashton.bradley> no, but it is imaginary time, so just trying to find a ground state.
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[slack] <ashton.bradley> error comp is important though, I agree
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[slack] <ashton.bradley> so if I dont use auto-sparsity, a sparse matrix gets treated as dense somehow?
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[slack] <chrisrackauckas> yes if it's an implicit method