Parallel pool never releases used memory leading to instability

Running code like:
rxs = rxsite("AntennaHeight",1.5, …
"Latitude", 38.9899587, "Longitude", -76.9353889);

for scenario = 1:2
switch scenario
% these are not meaningful paths
case 1
txPositions = [linspace(38.9857294, 38.9857294, 10000).’, linspace(-76.9442905, -76.9407240, 10000).’];
case 2
txPositions = [linspace(38.9895908, 38.9903186, 10000).’, linspace(-76.9432997, -76.9446669, 10000).’];
end

pm = propagationModel("raytracing");
data = [];
parfor point = 1:size(txPositions,1)
txs = txsite("AntennaHeight", 1.5, …
"Latitude", txPositions(1,point), "Longitude", txPositions(2,point), …
"TransmitterPower", 10);
rays = raytrace(txs, rxs, pm, "type", "power"); % rays is Na x Ns cell array
if ~isempty(rays{1}) % only ever 1 tx/1 rx
rayPower = 0;
% phasor sum of rec’d power
for rayPath = 1:numel(rays{1})
pWatts = 10^(-rays{1}(rayPath).PathLoss/10)*10;
rayPower = rayPower + pWatts*(cos(rays{1}(rayPath).PhaseShift) + 1i*sin(rays{1}(rayPath).PhaseShift));
end
% convert to RSS in dBm and resultant signal phase offset
RSS = 10*log10(abs(rayPower)/.001); % dBm
phaseOffset = angle(rayPower) ; % rads
% collate data
data = [samplePoints(step, 1), samplePoints(step, 2), RSS, phaseOffset];
end
end

close all force % this is an attempt to fix this issue
save("data.mat","data")
clear data
delete(gcp)

end
This code will spawn a transmitter, move it along a path, sample the RSS at a receiver then append that data into a list which gets saved. After that, the parallel pool is reinitialized and the data variable is cleared before starting the next scenario. The delete(gcp) line was from another about a similar issue which I cant find anymore – this helps but doens’t solve the problem.
Running this code, I would expect the memory usage to increase during a single scenario (which is what I see), but I would also expect to see memory usage drop considerably between scenarios. However, this code causes the memory usage to steadily increase across scenarios, regardless of if I delete the parallel pool and clear variables. This almost always results in MATLAB either locking up the computer or just crashing outright.
The issue never occurs on the first (or even the first few) scenario, but will always happen after some number have been run, so I know that the individual scenarios are totally fine.
Am I going about this wrong or is there something I should do to fix this? This issue is present on R2024b on Ubuntu22 and Win10.Running code like:
rxs = rxsite("AntennaHeight",1.5, …
"Latitude", 38.9899587, "Longitude", -76.9353889);

close all force % this is an attempt to fix this issue
save("data.mat","data")
clear data
delete(gcp)

end
This code will spawn a transmitter, move it along a path, sample the RSS at a receiver then append that data into a list which gets saved. After that, the parallel pool is reinitialized and the data variable is cleared before starting the next scenario. The delete(gcp) line was from another about a similar issue which I cant find anymore – this helps but doens’t solve the problem.
Running this code, I would expect the memory usage to increase during a single scenario (which is what I see), but I would also expect to see memory usage drop considerably between scenarios. However, this code causes the memory usage to steadily increase across scenarios, regardless of if I delete the parallel pool and clear variables. This almost always results in MATLAB either locking up the computer or just crashing outright.
The issue never occurs on the first (or even the first few) scenario, but will always happen after some number have been run, so I know that the individual scenarios are totally fine.
Am I going about this wrong or is there something I should do to fix this? This issue is present on R2024b on Ubuntu22 and Win10. Running code like:
rxs = rxsite("AntennaHeight",1.5, …
"Latitude", 38.9899587, "Longitude", -76.9353889);

close all force % this is an attempt to fix this issue
save("data.mat","data")
clear data
delete(gcp)

end
This code will spawn a transmitter, move it along a path, sample the RSS at a receiver then append that data into a list which gets saved. After that, the parallel pool is reinitialized and the data variable is cleared before starting the next scenario. The delete(gcp) line was from another about a similar issue which I cant find anymore – this helps but doens’t solve the problem.
Running this code, I would expect the memory usage to increase during a single scenario (which is what I see), but I would also expect to see memory usage drop considerably between scenarios. However, this code causes the memory usage to steadily increase across scenarios, regardless of if I delete the parallel pool and clear variables. This almost always results in MATLAB either locking up the computer or just crashing outright.
The issue never occurs on the first (or even the first few) scenario, but will always happen after some number have been run, so I know that the individual scenarios are totally fine.
Am I going about this wrong or is there something I should do to fix this? This issue is present on R2024b on Ubuntu22 and Win10. parallel computing MATLAB Answers — New Questions

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