MATLAB: Compare inv(X) Vs mex inv (X)

inv mex

Hi all
I wrote a simple program which calculates inverse matrix size (100*100).
function y = test_inv(x)   %#codegen
 % test inverse matrix
 y = inv(x);
end
I created mex function test_inv_mex and tested running time.
x = randn(100);
tic;
for n = 1: 100
    y = test_inv(x);
end
toc;
tic;
for n = 1: 100
    y = test_inv_mex(x);
end
toc;
This is my resulte :
Elapsed time is 0.054418 seconds.
Elapsed time is 0.613990 seconds.
My question is :
Why the mex function run much slower than regular one ?
B.R
Zohar

Best Answer

I think it's rather likely with a difference of that magnitude that you have left memory integrity checks on. Try
>> cfg = coder.config('mex');
>> cfg.IntegrityChecks = false;
>> cfg.ResponsivenessChecks = false;
>> codegen test_inv -args {zeros(100)} -config cfg
>> x = randn(100);
tic;
for n = 1: 100
    y = test_inv(x);
end
toc;
tic;
for n = 1: 100
    y = test_inv_mex(x);
end
toc;
Elapsed time is 0.082537 seconds.
Elapsed time is 0.109494 seconds.
The remaining difference is not surprising since there is some overhead and we are essentially just comparing the compiled and optimized MATLAB implementation to the compiled MATLAB Coder implementation. MATLAB Coder is not intended to speed up MATLAB linear algebra. They are mostly compiled and highly optimized routines. If it could do much of that, we'd just speed up the MATLAB implementation. If you want to see it speed something up, you usually need to have a substantial amount of your code in there. Also, in this particular case there are some differences in the algorithms. MATLAB Coder is generating unblocked code, and here the matrix is large enough that I would rather use a blocked algorithm.
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