Internal error with symbolic engine. Quit and restart MATLAB.

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Tony Cheng 2019-5-19

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https://ww2.mathworks.cn/matlabcentral/answers/462912-internal-error-with-symbolic-engine-quit-and-restart-matlab

评论： Tony Cheng 2019-6-2

Hi guys,

I am using symbolic math toolbox in Matlab 2018b in Win10 64-bit.

The problem is

Error mupadmex

Internal error with symbolic engine. Quit and restart MATLAB.

Error in sym/matlabFunction>mup2mat (line 404)

res = mupadmex('symobj::generateMATLAB',r.s,ano,spa,0);

Error in sym/matlabFunction>writeOutput (line 540)

body = mup2mat(y,false,sparseMat);

Error in sym/matlabFunction>writeMATLAB (line 453)

writeOutput(fid,outputs,f,1,sparseMat);

Error in sym/matlabFunction (line 183)

g = writeMATLAB(funs,file,varnames,outputs,body, opts.Optimize, opts.Sparse, opts.Comments);

Error in sym/odeFunction (line 135)

f = matlabFunction(expr, 'Vars', varsAndParams, matlabFunOptions{:});

Error in the_method_7 (line 180)

combined_mass_matrix_handle1 = odeFunction( Mrr , p_inde( 1 : 16 ) , 'Sparse' , true ,

'Optimize', false , 'File' , 'mass_matrix_file') ;

Are there any solutions to this? Many thanks!

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Walter Roberson 2019-5-31

I am using Mac.

MS Windows uses a page file, which is configured for a particular size rather than grown indefinitely.

https://www.geeksinphoenix.com/blog/post/2016/05/10/how-to-manage-windows-10-virtual-memory.aspx

With the memory exhaustion I was getting, I figured that the problem might just be too big to do all at once, and that plausibly you could run one conversion at a time, or perhaps a few together. I saved the elements of the 32 x 32 array into separate .mat files so I could reload them individually. I then told it to start converting the largest single one of them by itself.

The conversion ran for about 24 hours, without using excess memory during that time. However, a short time ago, my system started to slow down, and when I investigated I found that the mupad process was using little memory but that MATLAB was suddenly growing quickly in memory. When it got up to about 40-ish gigabytes, it crashed.

It is not expected that the mupad process would use so little memory, so I suspect I might have been looking at the mupad process for a different instance of MATLAB. I suspect that mupad crashed and that triggered MATLAB chewing up a bunch of memory and crashing. I will try converting a smaller one and see what happens.

Walter Roberson 2019-6-1

在 MATLAB Online 中打开

The conversion of Mrr(30,30) by itself is over 300 megabytes even though the .mat to store it is less than 31 kilobytes.

I was able to get the symbolic engine to write it out in a different format in "only" 50 minutes. It needs a bit of post-processing to use, but at the moment it looks like some auxillary functions might be enough, such as

function etc(various_arguments, qrf_dof_d3_in, qrf_dof_d4_in, more_arguments)
Im = @(v) imag(v);
conjugate = @(v) conj(v);
qrf_dof_d3 = @(t) qrf_dof_d3_in;
qrf_dof_d4 = @(t) qrf_dof_d4_in;

It is clear, however, that each evaluation of the system would take a fair bit of time, as there is probably a few gigabytes of expressions there. There are a lot of redundant calculations and the efficiency would probably be greatly improved by using the expression optimizer -- but the expression optimizer is very slow. It might be easiest to do the expression optimization in post-processing using text substitutions, such as calculating sin(qrf_dof_d4(t)) once and storing it in a variable and substituting that variable into the text of the expression.

Tony Cheng 2019-6-1

Dear Walter,

Thanks very very much for your great painstaking efforts, long time and patience for my problem! I really do not know how to express my appreciations to you in English or Chinese. Really beyong my speaking language...

Well, for this lenghty computation, I firmly believe that:

The computational procedure must be improved and simplified to save time, otherwise, the results can not be applied in the next stage in the project which needs realtime implementation.
Or, if what we want at the current stage is just the numerical values, we need a more powerful PC to do it.

Also, all our inputs are real-valued, we use " .' " to avoid the production of "conj" when transpose of a matrix is computed. Are there any other ways to avoid the unnecessary, annoying and time-consuming "conj" in our project?

BTW, I notice that in https://au.mathworks.com/help/symbolic/massmatrixform.html?s_tid=srchtitle

about massMatrixForm, matlabFunction is applied to compute ODEs.

Also, odeFunction is used to solve ODEs.

Here I am very curious, what the difference is using matlabFunction and odeFunction to reach the numerical solutions of ODEs? Is there any difference in accuracy, computational cost( e.g., time, RAM etc. ), or anything else?

In the end, 300 GB thanks to you, your Mac and your words!

Walter Roberson 2019-6-1

编辑：Walter Roberson 2019-6-1

Although the inputs might be real-valued, I see that the calculations involve complex values, and include taking real and imaginary parts of various expressions. It might be easier to leave the conj() in place.

I was able to write all of Mrr(30,30) to file in optimized form in slightly under 5 hours. The result was a much more reasonable 128 kilobytes instead of 325 megabytes. Execution time was about 0.0002 seconds per invocation. Without the optimization, execution time is about ... ummm, pretty long, I will update when I can manage to get a timing.

Your expressions have a mix of sizes, with some being constants (.mat file about 720 bytes), and some being small calculations (.mat file about 5 to 8 kilobytes) and some being large calculations (.mat file between 30 kilobytes and 60 kilobytes.) Mrr(30,30) is one of the smaller large calculations, with .mat file about 30 kilobytes.

This hints that although it might be time consuming, that it might be practical to write out the various entries one by one in optimized form.

However, when I looked at the generated code, I was reminded of a bug that I found in generating optimized files with matlabFunction: it does a whole bunch of calculations and messes up the final result, returning one of the intermediate results instead. At least as of R2019a, the result is not usable, at least not for long expressions such as these.

The difference between matlabFunction and odeFunction for this kind of input is that odeFunction converts function references such as qrf_dof_d3(t) into variables such as qrf_dof_d3 . After doing that, it passes the resulting expression into matlabFunction to do the code generation.

Would it be practical for you to upgrade to R2019a? There are some additional symbolic functions in R2019a that can make it easier to preprocess your functions for work-arounds.

Tony Cheng 2019-6-2

A possible solution.pdf

Hi Walter, today I have an idea in this trouble.

Because the symbolic expression of this problem is extraordinarily lengthy and complicated, and we have the initial values of the symbolic variables, Could we transfer them from symbolic expressions into numercial expressions before we use odeFunction, as shown in the attachment pdf file?

If yes, the computational burden can be alleviated a lot when sending relevant matrixes into odeFunction .

Many thanks for your great help!

Tony Cheng 2019-6-2