Why GPU performance is worse than CPU for this code?
1 vue (au cours des 30 derniers jours)
Afficher commentaires plus anciens
clear all
close all
tic
t=9999;
X = rand( t, 'single' );
G = gpuArray( X );
isequal( gather( G ), X ) % returns true
classUnderlying( G ) % returns 'single'
G2 = G .* G
toc
tic
X = rand( t, 'single' );
G1 = X;
G3 = G1 .* G1 ;
toc
The execution time of GPU is less than CPu i5. Would anybody answer it?
1 commentaire
Jan
le 27 Nov 2011
About "clear all" see: http://www.mathworks.com/matlabcentral/answers/16484-good-programming-practice#answer_22301
Please decide, if the "GPU performance is worse than CPU", or if "the execution time of GPU is less than CPU".
Réponse acceptée
Walter Roberson
le 27 Nov 2011
There is a lot of overhead for sending data to a GPU. It is only faster for sufficiently big matrices.
Also, in the first one you are including the "isequal" and the "classUnderlying" in the timing, neither of which is needed for the computation. It is not fair to time different sets of activities.
Plus de réponses (2)
Jan
le 27 Nov 2011
Please try this:
X = rand(1e3, 1e3, 'single' );
G = gpuArray( X );
G2 = G;
tic
for i = 1:100
G2 = G2 .* G;
end
toc
tic
G = X;
G2 = X;
for i = 1:100
G2 = G2 .* G;
end
toc
cdarling
le 19 Fév 2012
there is a possibility that your GPU supports parallel.gpu.GPUArray.rand(), and it would be much faster if you construct random numbers within GPU, instead of generate and copy them into GPU
0 commentaires
Voir également
Catégories
En savoir plus sur GPU Computing dans Help Center et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!