Much slower valid convolution using complementary size of kernels.

I am using the valid convolution using convn( T, a, 'valid').
I have run the code below:
T = randn(384,384,8);
a = randn(5,5,8);
b = randn(380,380,1);
tic; convn(T,a,'valid'); toc
tic; convn(T,b,'valid'); toc
The reuslt in my computer is
Elapsed time is 0.002837 seconds.
Elapsed time is 0.016301 seconds.
Thus the the latter is much slower compared to fomer one.
However, in terms of flops, or only in terms of multiplications
convn(T,a,'valid')
takes 5*5*8*(384-5+1)*(384-5+1)*(8-8+1) = 28880000 multiplications
convn(T,b,'valid')
also takes 380*380*1*(384-380+1)*(384-380+1)*(8-1+1) = 28880000 multiplications
So why are the two computing time so different?
And is there some ways to implement the convn(T,b,'valid') much faster?

3 Commenti

"So why are the two computing time so different?"
Just a guess but convn(T,a,'valid') possible more suitable to be parallelize since the result is (380 x 380) and each can be computed independently.
Whereas convn(T,a,'valid') is harder.
I understand your first point, this seems to infer that the difference between the two convolution using GPU will be more severe.
However, in which perspective convn(T,a,'valid') is harder? FLOPS? or hardware implementation?
No not FLOPS. As you said the FLOPS are more or less indentical.

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Risposte (3)

No, n-dimensional fourier-transforms, multiplication of the Fourier-transforms of 5-5-8 a with T will be a fair bit faster than the multiplication of the 380-by-380-by-1 b with T.
HTH
Roshan Hingnekar
Roshan Hingnekar il 22 Dic 2020
Modificato: Walter Roberson il 22 Dic 2020
T and 'a' are 3 dimensional where as 'b' is 2 dimensional, convolution of 3-dimensional with 2-dimensional will be slower than a 3-dimensional with a 3-dimensional.
refer to the below links for further insight on randn and convn functions.

1 Commento

I read the corredponding webpages, could you explain more on why the same dimensional convolution will be faster?

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I would suggest to do specific conv with MEX programing.
Not sure the chance to beat MATLAB though.

1 Commento

We once tried to write some C++ code to compete with matlab convn especially for 'valid' convolution, we found it really hard to beat Matalb convn. The matlab convn is really well-optimized.

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Prodotti

Release

R2020b

Richiesto:

il 13 Dic 2020

Modificato:

il 24 Dic 2020

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