Compare inv(X) Vs mex inv (X)

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

[Yash]

dont use INV, try some other option instaed of INV because if you use it, in newer version it gives that its old and try something diff apart from that

check out help*

• Y = inv(X) returns the inverse of the square matrix X. A warning message is printed if X is badly scaled or nearly singular.

In practice, it is seldom necessary to form the explicit inverse of a matrix. A frequent misuse of inv arises when solving the system of linear equations . One way to solve this is with x = inv(A)*b. A better way, from both an execution time and numerical accuracy standpoint, is to use the matrix division operator x = A\b. This produces the solution using Gaussian elimination, without forming the inverse. See \ and / for further information.

[Jan]

@zohar: Please explain, how you have "created the mex function". It matters if you have a hand-coded function, call the optimized ATLAS or BLAS functions, or if you let the code generator do this, which is implied by the comment "%#codegen" appearing in your code. Good answers require no guessing of important details.

@Yash: Without doubt you a right. But zohar's question concerned another topic.

[zohar]

Hi Yash,

I understand the disadvantage using inv(X).

Why the mex function run much slower than the regular one ?

[zohar]

Hi Jan,

I am new with codegen, but I saw that if I unchecked everything under project setting general the mex function run faster but still slower than regular one! (but warnnings appears ).

Any help ?

Answer 1

[Mike Hosea]

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.

[zohar]

Hi Mike, Thanks. +1