In March of 2020, there was a question about parfor loops and simbiology. (https://www.mathworks.com/matlabcentral/answers/510565-issues-with-doses-variants-in-parfor-loop-in-simbiology?s_tid=srchtitle)

I currently use a parfor loop, but my model is fairly large and uses a lot of molecules -- around 40 species and 40 reactions. As a result, it takes a very long time to obtain my results. I was wondering if you think SimFunction (along with 'UseParallel' and 'AutoAccelerate') would be appropriate for me to use. -- Below, you'll find that I use a parfor appoach and make sure the files are accessible through the latter two functions. After seeing the aforementioned post, I'm wondering if I should be using SimFunction, sbiosimulate, sbioaccelerate, sbioensemblerun, or another method to optimize my approach.

Here is the general structure for what I am trying to accomplish:

I am using SimBiology 2019b. The solver I need to use is SSA, monte carlo style. I have a chemical reaction network set up. I add an event at 3000 seconds to set the concentration of an 'input' species to a given value.

I have a species in the chemical reaction network that I view as the 'output' species. My goal is to run 100 simulations for each given input amount. Then, I would like to increase the input amount over 100 steps in a uniformly increasing manner at each step and observe the behavior of the 'output' species.

Here is the structure of my code:

for i = 1:100

sbioloadproject('model.sbproj');

cs = getconfigset(m1, 'default');

cs.SolverType = 'ssa';

solver = cs.SolverOptions;

solver.LogDecimation = 1000;

inputSpecies = sbioselect(m1,'Type','species','Name','inputSpecies');

inputSpecies.InitialAmount = 0;

parameterTimeunits = addparameter(m1,'Timeunits',1.0,'ValueUnits','minute','ConstantValue',true);

parameterMolunits = addparameter(m1,'Molunits',1.0,'ValueUnits','molecule','ConstantValue',true);

inputSpecies = addevent(m1, '(time/Timeunits) >= 3000', ['inputSpecies = (1500000*' num2str(i) ')*Molunits']);

sbiosaveproject modelParallel.sbproj m1 inputSpecies

clear m1;

parfor j=1:100

[m1,inputSpecies] = loadSimBiologyModel('modelParallel.sbproj');

[t,x,names] = sbiosimulate(m1);

parsave(['StochasticTest_Input' num2str(i) '_Instance' num2str(j)], inputSpecies, t, x, names);

end

end

function [m2,inputSpecies2] = loadSimBiologyModel(filename)

sbioloadproject(filename);

m2 = m1;

inputSpecies2 = inputSpecies;

end

function parsave(fname,inputSpecies,t,x, names)

save(fname,'inputSpecies','t','x','names');

end

With my current approach, I haven't become very familiar with parameters or doses. Would you be able to provide me some insights on A.) if SimFunciton (along with 'UseParallel' and 'AutoAccelerate') is appropriate and if so, B.) since the parameters and doses don't seem applicable to my setup, how can I adapt the function inputs appropriately? Any tips, suggestions, or critiques are happily welcomed. If you need any more info, please let me know.

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