fetchOutputs() results in an error when the preceding parfeval() was called using the backgroundPool

I have a code piece that works fine:

function [ServerVersInfo,VersInfoObtained,ExcInfo]=GetVersionInfoFromServer(URL)
    %init outputs 
    try
        %access server, update outputs accordingly
    catch ME
        %set fall-back values for outputs
    end
end

%calling code
p = gcp('nocreate');
if isempty(p)
    p = parpool('local',1);
end
FunHandle = parfeval(p,@GetVersionInfoFromServer,3,StoredUrl);

% wait until FunHandle.State is 'finished'...
[LatestVersInfo,VersInfoObtained,ExcInfo]=fetchOutputs(FunHandle);

When I just replace the pool from the parallel computing toolbox with the backgroundPool, the fetchOutputs throws a MATLAB:parallel:future:ExecutionErrors failure. What's the difference?

(P.S. I tried the backgroundPool because starting the pool from the parallel computing toolbox takes a huge amount of time...)

[Edric Ellis]

Can you show us the full error message you get from fetchOutputs? The error identifier you mention is a generic one that "wraps" all errors that happen on the workers. It's probable that the code you're trying to run on the workers isn't supported for thread-based pools - see the doc for more.

[Lionel Pöffel]

The failure message is the quite generic "One or more futures resulted in an error".

But you're right, the limitations described in the documentation will probably affect my use case as well.