Why GPU performance is worse than CPU for this code?

1 visualización (últimos 30 días)
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 comentario
Jan
Jan el 27 de Nov. de 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".

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Respuesta aceptada

Walter Roberson
Walter Roberson el 27 de Nov. de 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.

Más respuestas (2)

Jan
Jan el 27 de Nov. de 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
cdarling el 19 de Feb. de 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

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