why mexw64 generated by coder runs slower than pure .m file?

6 visualizaciones (últimos 30 días)
I'm recently learning how to use mex files. The case that I try to reproduce is from https://www.youtube.com/watch?v=TAKjSi-77Ns&list=PLcgIaTuuWp3kWI8d1C1wZDl0SfQDxm-CK&index=61. I tried to verify that mexw64 file genrated by coder runs faster than .m file.To my surprise, I followed the the lesson step by step, but the result was inconsistent. Here is the function:
function Sum = SUModd(N)
%#codegen
Sum=0; count=1;
while ne(count,N)
if ne(mod(count,2),0)
Sum=Sum+count;
else
Sum=Sum;
end
count=count+1;
end
end
Then I generated mexw64 file following the instructions, compared the execution time between the .m file and the .mexw64 file:
%% test the consuption time
clear all;
N=1e8;
t = cputime;
SUModd(N)
Tmat = cputime-t;
fprintf('M-file comp. Time is %5.5f sec \n',Tmat);
%% mex function generated from coder
T_mex = cputime;
SUModd_mex(N)
TT = cputime-T_mex;
fprintf('Mex-file comp. Time is %5.5f sec \n',TT);
the result confused me because mexw64 cost more time than pure matlab file which is inconsistent with video:
M-file comp. Time is 9.71875 sec
Mex-file comp. Time is 9.75000 sec
To find out what go wrong,I rewrite the SUModd function in C, and mex it:
#include "mex.h"
double summation(double N) {
// double N=1e8;
double sum = 0;
int cout = 1;
while (cout != N) {
if ((cout % 2) != 0) {
sum = sum + (double)cout;
}
else {
sum = sum;
}
cout = cout + 1;
// printf("%d \n",cout);
}
return sum;
}
void mexFunction(int nlhs,mxArray *plhs[],int nrhs,const mxArray *prhs[])
{
double x,result;
if (nrhs != 1)
mexErrMsgTxt("Wrong number of input arguments.\n");
// 检查输入变量数量是否正确,否则报错
if (nlhs > 1)
mexErrMsgTxt("Too many output argumnents.\n");
x = mxGetScalar(prhs[0]);
// result = summation(x);
double *finaldata;
plhs[0] = mxCreateDoubleMatrix(1,1,mxREAL);
finaldata = mxGetPr(plhs[0]);
finaldata[0] = summation(x);
}
the time consuption was just 0.12500 sec which was consistent with the video.
So my question is: Why the mexw64 file generated by coder didn't improve the computational efficiency? Or Did I missed some details when I ws using coder?

Respuesta aceptada

David Fink
David Fink el 4 de Sept. de 2022
The C code generated by MATLAB Coder can be found in the codegen/mex/SUModd/ folder, so you can compare that against the handwritten version.
Various configuration options affect the generated code and C compiler options, including IntegrityChecks, ResponsivenessChecks, EnableDebugging, EnableMexProfiling, etc. See the full list of options on the coder.MexCodeConfig page:
If the generated code is missing an optimization opportunity, please report this to MathWorks Technical Support:
In general, measuring the performance of generated code will be more accurate by using "tic" and "toc" calls inside the function, since this won't include the overhead of passing input and output data between MATLAB and the generated code. However, in this case (double -> double), that overhead should be tiny.
  10 comentarios
zhou caiwei
zhou caiwei el 15 de Sept. de 2022
Alright, Is there a generic mexFunction template or built-in function to compile the converted C\C++ code into mex files?
zhou caiwei
zhou caiwei el 15 de Sept. de 2022
Because somehow the mex file directly converted from the matlab file is very inefficient.

Iniciar sesión para comentar.

Más respuestas (0)

Categorías

Más información sobre MATLAB Coder en Help Center y File Exchange.

Etiquetas

Productos


Versión

R2021b

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by