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Issues with doses/variants in parfor loop in SimBiology

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emjey on 12 Mar 2020
Commented: emjey on 20 Mar 2020
I have a question about runing the sbproj models in parfor loop
1. I load project and set up the solver:
csObj = getconfigset(m1);
csObj.SolverType = 'sundials';
csObj.SolverOptions.AbsoluteToleranceScaling = 1;
csObj.SolverOptions.AbsoluteTolerance = 1E-16;
csObj.SolverOptions.RelativeTolerance = 1E-12;
csObj.MaximumWallClock = 60;
2. I define dose and variant:
dose1 = getdose(m1,'myDose1');
v1 = getvariant(m1,'myVariant1');
3. accelerate the model
4. simulate in parfor loop
m1ParConst = parallel.pool.Constant(m1);
parfor i = 1:r
% dose1 = getdose(m1ParConst.Value,'rela_3mgpkg_80kg_q2wx31');
% v1 = getvariant(m1,'myVariant1');
[t,y] = sbiosimulate(m1ParConst.Value,[],v1,dose1);
Q1. Is this correct? If I include dose1 and v1 definition (i.e. if I uncomment dose1 and v1 in parfor loop) I get an error:
Undefined function 'getdose' for input arguments of type 'double'.
Error in parallel_function>make_general_channel/channel_general (line 923)
O = F(C{:});
Error in remoteParallelFunction (line 46)
out = parallel.internal.pool.serialize(feval(channel, channelArgs{:}));
Q2: are the solver settings respected? If I try to include csOBj in 'sbiosimulate' call I get an error as well.


emjey on 12 Mar 2020
R2018b, I have to check if I can switch to later version but for now I have this setup and it would be great if I can get it to work.
Update: I am installing R2019b now and keep you posted what happens.

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Answers (1)

Arthur Goldsipe
Arthur Goldsipe on 12 Mar 2020
First, what version of SimBiology are you using? Prior to R2019b, there was a problem that prevented objects from getting sent to workers properly. That is usually the cause of errors like "Undefined function 'getdose' for input arguments of type 'double'."
Second, it can be difficult to get details right with acceleration and parallelization when using sbioaccelerate and sbiosimulate. For example, sbioaccelerate is a "local" operation that is not preserved when transferring a model across workers. So if you want an accelerated model on a worker, you have to run sbioaccelerate on that worker.
As an alternative, I recommend using a SimFunction instead. It takes care of all of these details and is generally faster and more efficient. Let me show you some sample code. For now, I will assume you want to simulate varying the values of parameters p1 and p2, and look at the simulation results for y1 and y2. (You can also vary the dosing, or specify your alternate paramaeters using variants.)
1. Load project and set up the solver:
csObj = getconfigset(m1);
csObj.SolverType = 'sundials';
csObj.SolverOptions.AbsoluteToleranceScaling = 1;
csObj.SolverOptions.AbsoluteTolerance = 1E-16;
csObj.SolverOptions.RelativeTolerance = 1E-12;
csObj.MaximumWallClock = 60;
tStop = csObj.StopTime;
2. Define dose and parameter values:
dose1 = getdose(m1,'myDose1');
doseTable = getTable(dose1);
p1 = [1;2;3];
p2 = [4;5;6];
3. Create the SimFunction (ignoring any warning about the dose):
func = createSimFunction(m1, ["p1", "p2"], ["y1", "y2"], dose1, "UseParallel", true);
4. Simulate in parallel:
[timeCell, yCell] = func([p1 p2], tStop, doseTable);


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emjey on 17 Mar 2020
Apologies Arthur for the delay. For start I would like to be able to use efficienlty the R2019b version but I ran into problems.
In the meantime I've experimented with 'parfor' simulation of the 'AntibacterialPKPD.sbproj' model which I extended a bit, added one long dosing, 'myDose', and increased the simulation time accordingly. I did that to test/learn acceleration and parallel setup.
As you can see from the figures, there is no speedup in the accelerated version. For 25 loops, each with 11 simulations, takes
  • 5.72 min with an apparently accelerated model
  • 6.0 min with a non-accelerated model
It must be something I get wrong in the script, AntibacterialPKPD_PARFOR.m. Attached 1) sbproj file, 2) parameter file, 3) M-file.
Any comments would be very appreciated.
Sietse Braakman
Sietse Braakman on 19 Mar 2020
This problem does not exist in MATLAB/SimBiology version R2019b and later.
Prior to 19b, SimBiology objects are not automatically transferred to the workers when a parfor loop is used. You can circumvent this storing the necessary objects in the parallel.pool.Constant. Once you have 'unpacked the parallel.pool.Constant values for each worker, you can accelerate the model inside the parfor loop. Alternatively, you can create a simfunction outside the parfor loop, attach that to the parallel.pool.Constant and then use the simfunction inside the parfor loop. I have attached an updated version of your script. Note that I expected the simfunction to give me the same values of Drug.Central at t = 3360 as the sbiosimulate approach but this doesn't seem to be the case. You will need to check what's going on there, but at least you'll be able to see how to use the simfunction in this case. Perhaps I switched a parameter order or dimension of C around?
I am posting the relevant additions/changes below. Let me know if that works.
loopTimeTot = zeros(r,p+1);
params = sbioselect(m1,'Where','Name','==',paramsDF.parameter);
simfun = createSimFunction(m1,paramsDF.parameter,varName,d1.TargetName);
c = parallel.pool.Constant({m1,simfun});
accTimes = nan(r,1);
parfor i = 1:r
%%%%%%%%%%% SETUP %%%%%%%%%%%
model = c.Value{1}; % grab model from parallel.pool.Constant
dose = getdose(model,'myDose'); % extract dose from model
configset = getconfigset(model); % extract configset from model
% start acceleration, note that the acceleration is only performed once
% on each worker.
% inputs for simfunction
simfunction = c.Value{2}; % grab simfunction from parallel.pool.Constant
doseTable = getTable(dose); % create a table from the dose object
stopTime = configset.StopTime; % grab the stoptime from the configset
[t,y] = simfunction(C,stopTime,doseTable);
emjey on 20 Mar 2020
Thank you, it works indeed for the example model. Acceleration brings the simulation time down to 20% of the default one!

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