N dimensional multiplication on gpu arrays

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ahmet keles
ahmet keles am 7 Dez. 2022
Kommentiert: Joss Knight am 17 Dez. 2022
Is there a better way to compute N dimensional multiplication faster on gpu arrays? I am trying to write a custom deep learning layer which works with gpu array data. However this calculation takes too long for the layer to be meaningfull. Is there a way to do element wise multiplication like this one better on gpu arrays?
A=gpuArray(rand(20,20,16,1000));
B=gpuArray(rand(16,1000));
Z=zeros(size(A),'like',A);
tic
for i=1:16
for j=1:1000
Z(:,:,i,j)=A(:,:,i,j).*B(i,j);
end
end
toc
  1 Kommentar
ahmet keles
ahmet keles am 7 Dez. 2022
I have found a clever way to do it. Convert the small matrix into N dimensional array and multiply.
A=gpuArray(rand(20,20,16,10));
B=gpuArray(rand(16,10));
C=Matrisize(B,A);
Z=A.*C;
function [C]=Matrisize(X1,X2)
S=size(X2);
C=zeros(size(X2),'like',X2);
for i=1:S(1)
for j=1:S(2)
C(i,j,:,:)=X1;
end
end
end

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C B
C B am 7 Dez. 2022
It is possible to improve the performance of the code you have provided by using the built-in element-wise multiplication operator .* in MATLAB, instead of the loop you are currently using. This operator can automatically take advantage of the parallel processing capabilities of the GPU, allowing for faster computation.
Here is an example of how you can use .* to perform element-wise multiplication of the A and B arrays on the GPU:
% Create gpuArray arrays
A = gpuArray(rand(20,20,16,1000));
B = gpuArray(rand(16,1000));
% Perform element-wise multiplication using .*
Z = A .* B;
Using this approach, the multiplication operation will be performed in parallel on the GPU, which should provide a significant performance improvement compared to using a loop.
Alternatively, you can use the built-in times function to perform element-wise multiplication on the GPU. This function has the same effect as the .* operator, but is written as a function rather than an operator. Here is an example of how to use times to perform element-wise multiplication on the GPU:
% Create gpuArray arrays
A = gpuArray(rand(20,20,16,1000));
B = gpuArray(rand(16,1000));
% Perform element-wise multiplication using times
Z = times(A, B);
Both of these approaches should provide significant performance improvements compared to using a loop to perform element-wise multiplication on the GPU.
  2 Kommentare
ahmet keles
ahmet keles am 7 Dez. 2022
Arrays have incompatible sizes for direct element wise multiplication thats the problem
Joss Knight
Joss Knight am 17 Dez. 2022
B = gpuArray(rand(1,1,16,1000)) is what you need here.

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